Minimizing the sum of the squared deviations around the line is called Least square estimation.
It is given that the sum of squares is around the line.
Least squares estimations minimize the sum of squared deviations around the estimated regression function. It is between observed data, on the one hand, and their expected values on the other. This is called least squares estimation because it gives the least value for the sum of squared errors. Finding the best estimates of the coefficients is often called “fitting” the model to the data, or sometimes “learning” or “training” the model.
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The greatest GCF would be
Answer:
The boat traveling at 24 kph when John goes downstream.
Step-by-step explanation:
We are given the following in the question:
John has a boat that will travel at the rate of 15 kph in still water.
Let x be the speed of the current.
Speed of boat in upstream

Speed of water in downstream

Relation:

We have to find the speed of boat in downstream.
Time to travel upstream for 35 km = Time to travel 140 km downstream

Thus, speed of current is 9 kph.
Speed of boat in downstream = 15 + 9 = 24 kph.
Thus, the boat traveling at 24 kph when John goes downstream.
Answer:
Increasing if f' >0 and decreasing if f'<0
Step-by-step explanation:
Difference quotient got by getting
will be greater than 0 if function is increasing otherwise negative
Here h is a small positive value.
In other words, we find that whenever first derivative of a function f(x) is positive the function is increasing.
Here given that for x1, x2 where x1<x2, we have
if f(x1) <f(x2) then the function is decreasing.
Or if x1<x2 and if f(x1) >f(x2) for all x1, and x2 in I the open interval we say f(x) is decreasing in I.
Answer: Length = 24; width =4
Step-by-step explanation
Since the ratio of the length to width is 6:1
Let the length be represented as 6x
And the width be = x
Such that that the Perimeter of the rectangle which is
Perimeter = 2(length + width) becomes
56 = 2(6x + x)
56/2 = 6x+x
28 = 7x
x = 4
Width = 4
Length = 6x= 6 x 4 = 24